feat: Implement unified memory management for ONNX model inference

- Introduced a new memory management policy for ONNX Runtime to release temporary GPU memory after inference completion.
- Established a shared inference entry point for all ONNX models, differentiating between long-lived sessions and temporary memory arenas.
- Updated CUDA sessions to utilize a shrinkable memory arena, reclaiming GPU memory post-inference.
- Ensured consistent memory release semantics across BEN2, DA3, MoGe-2, and Upscale models while reusing existing sessions.
- Added lifecycle tests to validate temporary memory release and session reuse.
- Modified model adapters to integrate the new memory management features, ensuring backward compatibility with existing inference behavior.
- Enhanced unit tests to cover new memory release scenarios and verify correct behavior across different execution providers.

tests/test_model_upscale_onnx.py

@@ -2,6 +2,7 @@ import sys
 import unittest
 from pathlib import Path
 from types import SimpleNamespace
+from unittest.mock import patch
 
 import numpy as np
 from PIL import Image
@@ -20,6 +21,9 @@ import onnx_upscale
 
 
 class FakeSession:
+    def get_providers(self):
+        return ["CPUExecutionProvider"]
+
     def get_inputs(self):
         return [SimpleNamespace(name="input")]
 
@@ -121,6 +125,40 @@ class UpscaleOnnxTest(unittest.TestCase):
         self.assertEqual(session.calls, 6)
         self.assertEqual(session.feeds["input"].shape, (1, 3, 256, 256))
 
+    def test_only_final_tile_releases_memory(self):
+        releases = []
+        session = FakeSession()
+
+        def run(model, output_names, feeds, *, release_memory):
+            releases.append(release_memory)
+            return model.run(output_names, feeds)
+
+        with patch.object(onnx_upscale, "run_session", side_effect=run):
+            result = onnx_upscale.infer(
+                session,
+                Image.new("RGB", (449, 225), (1, 2, 3)),
+            )
+
+        self.assertEqual(result.size, (1796, 900))
+        self.assertEqual(releases, [False, False, False, False, False, True])
+
+    def test_non_final_image_does_not_release_its_final_tile(self):
+        releases = []
+        session = FakeSession()
+
+        def run(model, output_names, feeds, *, release_memory):
+            releases.append(release_memory)
+            return model.run(output_names, feeds)
+
+        with patch.object(onnx_upscale, "run_session", side_effect=run):
+            onnx_upscale.infer(
+                session,
+                Image.new("RGB", (449, 225), (1, 2, 3)),
+                release_memory=False,
+            )
+
+        self.assertEqual(releases, [False] * 6)
+
     def test_provider_unicode_error_is_presented_as_resource_error(self):
         class InvalidProviderSession(FakeSession):
             def run(self, _output_names, _feeds):